import cv2 as cv
import numpy as np

# The video feed is read in as
# a VideoCapture object
cap = cv.VideoCapture("test.mp4")

# ret = a boolean return value from
# getting the frame, first_frame = the
# first frame in the entire video sequence
ret, first_frame = cap.read()

# Converts frame to grayscale because we
# only need the luminance channel for
# detecting edges - less computationally
# expensive
prev_gray = cv.cvtColor(first_frame, cv.COLOR_BGR2GRAY)

# Creates an image filled with zero
# intensities with the same dimensions
# as the frame
mask = np.zeros_like(first_frame)

# Sets image saturation to maximum
mask[..., 1] = 255.0

while (cap.isOpened()):

    # ret = a boolean return value from getting
    # the frame, frame = the current frame being
    # projected in the video
    ret, frame = cap.read()

    # Opens a new window and displays the input
    # frame
    cv.imshow("input", frame)

    # Converts each frame to grayscale - we previously
    # only converted the first frame to grayscale
    gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)

    # Calculates dense optical flow by Farneback method  dx/dt  dy/dt
    flow = cv.calcOpticalFlowFarneback(prev_gray, gray,
                                       None,
                                       0.5, 3, 15, 3, 5, 1.2, 0)

    # Computes the magnitude and angle of the 2D vectors
    magnitude, angle = cv.cartToPolar(flow[..., 0], flow[..., 1])

    # Sets image hue according to the optical flow
    # direction
    # mask[..., 0] = angle * 180 / np.pi / 2
    mask[..., 0] = angle * 180 / np.pi
    # mask[..., 0] = angle
    direct = mask[..., 0]

    # Sets image value according to the optical flow
    # magnitude (normalized)
    mask[..., 2] = cv.normalize(magnitude, None, 0, 255, cv.NORM_MINMAX)
    strong90 = np.percentile(mask[..., 2], 80)
    strong = mask[..., 2]
    shape = mask.shape
    if strong90 > 0:
        l = np.where(mask[:, :, 2] > strong90, mask[:, :, 0], 0)
        l1=l[l>0]
        print(222, np.mean(l1))

    # Converts HSV to RGB (BGR) color representation
    rgb = cv.cvtColor(mask, cv.COLOR_HSV2BGR)

    # Opens a new window and displays the output frame
    cv.imshow("dense optical flow", rgb)

    # Updates previous frame
    prev_gray = gray

    # Frames are read by intervals of 1 millisecond. The
    # programs breaks out of the while loop when the
    # user presses the 'q' key
    if cv.waitKey(1) & 0xFF == ord('q'):
        break

# The following frees up resources and
# closes all windows
cap.release()
cv.destroyAllWindows()
